Conventional Unmanned Aerial Vehicles (UAVs) operate in various environments and terrains. Future UAV teams are envisioned to be highly autonomous, not requiring constant attention from a control station. These autonomous UAV teams will likely communicate over a radio frequency link with the control base station. If several autonomous UAVs are operating as part of a team, these UAV team members will likely communicate with each other over a communication network as well. These UAV members will likely be required to inform each other of their respective and absolute positions and flight plans so that they operate in a coordinated manner and, since these UAV members are operating autonomously, to continually adjust flight plans to react to the environment, the terrain, and to enemy threats. Each UAV member in the team would communicate at unpredictable times with other members of the team asynchronously.
Sometimes a UAV using the most available data rate may not be the UAV with the highest priority, or critical mission need. At worst, the degradation of communications may persist for a period that may degrade the UAV team's critical mission effectiveness.
Autonomous systems also may be desired to be aware of their environment and adapt plans based on changes in their understanding of their environment. Control, therefore, must be flexible, both in development and in execution. A autonomous system may be given objectives to achieve. These objectives may be as simple as monitor state and report problems, or complex, for example, assault and capture a target area.
Additionally, the system may be given constraints such as flight corridors, acceptable risk, or authorized targets. A challenge may be to meld these objectives and constraints with the environmental state and the system state to plan and execute a mission plan in order to achieve the given objectives without violating the constraints.
Furthermore, an autonomous system may itself consist of autonomous subsystems. Thus, the autonomy may also be collaborative, coordinating multiple autonomous subsystems (i.e., vehicles, etc.) to act as a single system. In addition, a team of unmanned vehicles may have access to assets external to the team that would aid in performance and execution of the mission plan. These assets may also be used in concert with the team.
Conventional approaches focus on individual autonomy, ignoring an important facet of collaborative autonomy. It is advantageous to intermingle collaborative aspects into an autonomous system sooner rather than later because many environmental factors may change in a collaborative environment.
For example, a system planning for a team of autonomous assets may evaluate heterogeneous and dynamic asset attributes that may themselves execute autonomous decisions based on previously unknown information thereby impacting a team's mission plan. It would be advantageous for team planning to recognize and process this impact.
Conventional approaches are monolithic (i.e., a single control system that performs all the functions required). This approach fails to recognize different disciplines needed to perform the various functions. For example, the conventional system requires awareness of its environment. Thus, the conventional system may need to both estimate probabilities in a data rich environment and optimize courses of action from those estimates for effecting a change to the data rich environment.